How CSP Labs Improved 100-Seed-Weight Processing by 70%
At CSP Labs, operational improvements often come from refining the everyday laboratory workflows that support sample processing and turnaround times. While many advancements in the laboratory focus on expanding testing capabilities or implementing new technologies, workflow improvements at the operational level can also have a significant impact across higher-volume processing environments.
One recent example is an internally developed AI-assisted seed counting workflow designed to improve 100-seed-weight processing. This workflow was developed to reduce manual seed counting time while supporting more consistent processing across larger sample volumes. Traditionally, laboratory staff manually counted exactly 100 seeds before recording the sample weight and calculating the corresponding 100-seed-weight value. While straightforward, the process is repetitive and time-intensive when performed continuously across large numbers of samples.
To improve efficiency, CSP Labs developed an imaging-based workflow that combines automated seed detection with scale-reading analysis. The process begins by placing ~100-110 seeds on a scale and capturing images of both the sample and the visible scale reading. Once uploaded, the images are processed through an internally developed workflow that detects the number of seeds present and automatically calculates the corresponding 100-seed weight. The system combines automated sample ID and seed detection with integrated scale-reading analysis to generate 100-seed-weight calculations efficiently and consistently. Following processing, laboratory staff review the generated information and submit the finalized data directly into our LIMS along with an automatically generated audit ready PDF report.
Captured Sample Image
Processed Seed Detection
Improving Seed Processing Workflow Efficiency
The updated workflow reduced processing time from approximately two minutes per sample to roughly 20 to 30 seconds. While the time savings per sample may appear modest individually, the operational impact becomes much more meaningful across high-volume laboratory workflows where repetitive processing steps are performed continuously throughout the day. Reducing manual counting steps helps improve sample throughput and processing consistency, while also allowing laboratory staff to spend less time on repetitive tasks and more time supporting other operational priorities throughout the laboratory.
This project is one example of how CSP Labs continues to invest in practical workflow improvements that support laboratory operations and turnaround efficiency. “Ultimately, improvements like this help support turnaround times while maintaining accuracy throughout the counting process,” said Nilesh Maharaj, Laboratory Director at CSP Labs. As laboratory demands continue to evolve, CSP Labs remains focused on identifying practical ways to improve operational efficiency and workflow performance across the organization.
